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import gradio as gr
from transformers import pipeline
languages = [
"Arabic", "Basque", "Breton", "Catalan", "Chinese_China", "Chinese_Hongkong",
"Chinese_Taiwan", "Chuvash", "Czech", "Dhivehi", "Dutch", "English",
"Esperanto", "Estonian", "French", "Frisian", "Georgian", "German", "Greek",
"Hakha_Chin", "Indonesian", "Interlingua", "Italian", "Japanese", "Kabyle",
"Kinyarwanda", "Kyrgyz", "Latvian", "Maltese", "Mongolian", "Persian", "Polish",
"Portuguese", "Romanian", "Romansh_Sursilvan", "Russian", "Sakha", "Slovenian",
"Spanish", "Swedish", "Tamil", "Tatar", "Turkish", "Ukranian", "Welsh"
]
pipe = pipeline("text-classification", model="Mike0307/multilingual-e5-language-detection")
def func(inp):
result = ''
out = pipe(inp)
for lang in out:
result += languages[int(lang['label'][6:])] + ' ' + str(lang['score']) + '\n'
return result
demo = gr.Interface(fn=func, inputs="text", outputs="text")
demo.launch() |